CN109376257A - Tealeaves recognition methods based on image procossing - Google Patents
Tealeaves recognition methods based on image procossing Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/155—Segmentation; Edge detection involving morphological operators
Abstract
The tealeaves recognition methods based on image procossing that the invention discloses a kind of, (A1) obtain the RGB original color image of sample tealeaves, tea stalk and yellow leaf；(A2) RGB original color image is made into filtering and noise reduction pretreatment；(A3) hsv color space will be transformed into from RGB color by pretreated RGB original color image form HSV color image；(A4) the tone H of tealeaves, tea stalk and yellow leaf HSV color image, the characteristic parameter of saturation degree S, lightness V are extracted；(A5) according to the characteristic parameter of the tone H of tealeaves, tea stalk and yellow leaf, saturation degree S, lightness V, the upper and lower limit value of respective tone H, saturation degree S, lightness V are determined, so that it is determined that the respectively value range of tone H, saturation degree S, lightness V；(A6) by the tea dry sorting control system of determining value range typing tea dry sorting equipment, database is constituted；B, the acquisition of characteristics of objects parameter；C, the matching of characteristic parameter.This method can rapidly sort out the tea stalk in tealeaves, yellow leaf.
Description
Technical field
The present invention relates to a kind of tealeaves recognition methods, especially a kind of tealeaves recognition methods based on image procossing.
Background technique
Image processing techniques is the development and an important applied field that is mature and developing rapidly with computer,
It is simulation eye recognition mechanism, using color as a kind of technical method of main characteristic parameters.With computer image processing technology
The intelligent operation of information collection and processing can be achieved, and lossless, quick, real-time monitoring is carried out to identification object, improve and calculate
The precision and efficiency of method are widely used to production and the manufacture field of modern agriculture.
In recent years, many scholars are dedicated to the research of tealeaves identification, and some scholars utilize the color characteristic pair of color image
Tealeaves tender leaf is identified；Another part scholar identifies the finished tea after processing using image processing techniques.
In the identification to finished tea, someone identifies tealeaves using near-infrared spectrum technique, and someone is known using BP neural network technology
Other tealeaves, there are also groups of people, and tealeaves is identified using support vector machines, and recognition effect is preferable, but these methods are that identification is different
The method of type tealeaves carries out identification to same tealeaves to screen tealeaves, tea stalk and the yellow leaf in same tealeaves
Method out rarely has people's research.
Summary of the invention
The tealeaves recognition methods based on image procossing that the object of the present invention is to provide a kind of.This method can be to tealeaves
It is monitored, lossless, rapidly can be sorted out the tea stalk in tealeaves, yellow leaf in real time.
Technical solution of the present invention: a kind of tealeaves recognition methods based on image procossing, this method include building for database
The vertical, acquisition of characteristics of objects parameter and the matching of characteristic parameter, specific steps include:
A, the foundation of database
(A1) the RGB original color image of sample tealeaves, tea stalk and yellow leaf is obtained；
(A2) RGB original color image is made into filtering and noise reduction pretreatment；
(A3) HSV color space will be transformed into from RGB color by pretreated RGB original color image form HSV
Color image；
(A4) the tone H of tealeaves, tea stalk and yellow leaf HSV color image, the characteristic parameter of saturation degree S, lightness V are extracted；
(A5) according to the characteristic parameter of the tone H of tealeaves, tea stalk and yellow leaf, saturation degree S, lightness V, respective tone is determined
H, the upper and lower limit value of saturation degree S, lightness V, so that it is determined that the respectively value range of tone H, saturation degree S, lightness V；
(A6) by the tea dry sorting control system of determining value range typing tea dry sorting equipment, database is constituted；
B, the acquisition of characteristics of objects parameter
Tealeaves to sub-sieve is put into tea dry sorting equipment, in tealeaves transmission process, step (A1) is repeated to (A4), passes through
The characteristic parameter of tea dry sorting control system acquisition object；
C, the matching of characteristic parameter
The characteristic parameter for the object that will acquire is matched with the value range of tealeaves, tea stalk and yellow leaf in database, is confirmed
Object belongs to tealeaves, tea stalk, yellow leaf or other.
The RGB original color image acquisition methods of tealeaves recognition methods above-mentioned based on image procossing, object are, will be at
Leaf of sampling tea is put on a vibrator platform, and as vibrator vibrates, finished tea is 30 ° -70 ° of skewed slot along gradient
Even drop down obtains RGB original color image by CCD color camera into the shooting area of CCD color camera.
Tealeaves recognition methods above-mentioned based on image procossing, in the RGB original color image acquisition process of object, skewed slot
Place plane is vertical with the camera plane of CCD color camera, and skewed slot is black with space wall locating for CCD color camera entirely
Color.
Tealeaves recognition methods above-mentioned based on image procossing, in the RGB original color image acquisition process of object, CCD
For the background of color camera using flannelette acrylic board as background board, light source uses colour temperature for the area source of 5000k-6000k.
Tealeaves recognition methods above-mentioned based on image procossing, in the RGB original color image acquisition process of object, recruitment
The finished tea of camera imaging area is passed through in the shooting of industry line array CCD color camera, its pixel data is obtained, then by pixel data
It carries out inputting tea dry sorting control system after processing is converted into RGB original color image.
Tealeaves recognition methods above-mentioned based on image procossing, the specific side of RGB original color image filtering and noise reduction pretreatment
Method is to be filtered noise suppression preprocessing to RGB original color image using adaptive-filtering and histogram equalization method.
Tealeaves recognition methods above-mentioned based on image procossing, in the acquisition process of characteristics of objects parameter, the feature of object
After parameter obtains, by Morphological scale-space, region ineligible in HSV color image is eliminated, and will be eligible
Characteristics of image identify, then qualified image features are matched with database again.
Tealeaves recognition methods above-mentioned based on image procossing, after the RGB original color image of object obtains, by it
It is input in tea dry sorting control system and is handled, extract the characteristic parameter based on HSV color image.
Tealeaves recognition methods above-mentioned based on image procossing, step C, in the matching process of characteristic parameter, the category of object
Property confirmation after, tea dry sorting control system control one group high speed spray valve events, using high speed spray valve change yellow leaf, tea stalk and
The direction of other materials landing, so that tealeaves, tea stalk, yellow leaf and other materials are landed from different channels.
Tealeaves recognition methods above-mentioned based on image procossing, the high speed spray valve and tealeaves feed chute are coplanar, position
In the flat lower section in camera shooting area.
Beneficial effects of the present invention: compared with prior art, the present invention is based on the tealeaves recognition methods of image procossing, are mentioning
Hsv color model is selected when taking tealeaves Color characteristics parameters, and extracts tealeaves, tea in color image H, S, V triple channel respectively
Stalk, yellow leaf characteristic parameter, while determine tea stalk and yellow leaf H, S, V value range, by by the characteristic parameter of object be worth model
Enclose and matched, thus by image multiple tea stalks and yellow leaf all identify, realize tealeaves identification automation, energy
It is enough in real time in tealeaves tea stalk and yellow leaf be monitored, tealeaves will not be damaged in entire assorting room, Er Qiefen
Select fast speed.It is identical using the COMPUTER DETECTION result that this method carries out with artificial detection result.
Detailed description of the invention
Fig. 1 is the color identification process figure of finished tea；
Fig. 2 be tealeaves, tea stalk, yellow leaf original image；
Fig. 3 is the channel HSV color image H pixel distribution；
Fig. 4 is the recognition result of tea stalk, yellow leaf.
Specific embodiment
The present invention is further illustrated with reference to the accompanying drawings and examples, but be not intended as to the present invention limit according to
According to.
The embodiment of the present invention: a kind of tealeaves recognition methods based on image procossing, as shown in attached drawing 1-4, this method packet
Include the foundation of the database of tealeaves, tea stalk and yellow leaf in known finished tea, the acquisition and characteristics of objects of characteristics of objects parameter
The matching of parameter, specific steps include:
A, in known finished tea the database of tealeaves, tea stalk and yellow leaf foundation
(A1) in same kind of finished tea, the finished tea sample of multiple batches is chosen, should be wrapped in the finished tea sample
Tealeaves, tea stalk and yellow leaf are included, and by all artificial separation of tealeaves, tea stalk and the yellow leaf in each sample, is individually stored, so
The RGB original color image of tealeaves in each batch sample, tea stalk and yellow leaf is obtained afterwards；
(A2) numerous RGB original color images is made into filtering and noise reduction pretreatment respectively；
(A3) HSV color space will be transformed into from RGB color by pretreated RGB original color image form HSV
Color image；
(A4) tealeaves, tea stalk and yellow leaf are extracted in the tone H of HSV color image, saturation degree S, these three channels lightness V
Characteristic parameter；
(A5) according to the characteristic parameter of the tone H of tealeaves, tea stalk and yellow leaf, saturation degree S, lightness V, determine tealeaves, tea stalk with
And the upper and lower limit value of the respective tone H of yellow leaf, saturation degree S, lightness V, so that it is determined that tealeaves, tea stalk and the respective color of yellow leaf
Adjust the value range of H, saturation degree S, lightness V；
(A6) by the tea dry sorting control system of the value range typing tea dry sorting equipment of determining tealeaves, tea stalk and yellow leaf
In, database is constituted, and saved.
After finished tea is based on the characteristic parameter Database of HSV color image, it can start to carry out based on the number
According to the sub-sieve work of the finished tea in library.Sub-sieve work mainly includes several steps: firstly, being each in acquisition finished tea
The characteristic parameter of a component part；Secondly, the characteristic parameter that will acquire is matched with the value range in database, the spy is confirmed
Sign parameter is fallen into that value range, to confirm the attribute of the corresponding object of this feature parameter.So far, entire finished tea
Identification process finish.
But the identification process of finished tea can only finally confirm in finished tea which be tealeaves, which be tea
Stalk, which be yellow leaf, be other materials there are also those.The identification of finished tea is finally that the sorting to tealeaves provides service, most
In whole assorting room, early-period confirmation is crossed to the finished tea of attribute by mechanical action, be divided into tealeaves, tea stalk, yellow leaf and
Other four classifications, the substance of four classifications is collected together respectively.
B, in finished tea characteristics of objects parameter acquisition
Finished tea to sub-sieve is put into tea dry sorting equipment, in tealeaves transmission process, is repeated step (A1) to (A4),
The characteristic parameter based on HSV color image of object is obtained by tea dry sorting control system；
C, the matching of characteristics of objects parameter
The value model of tealeaves, tea stalk in the characteristic parameter and database of the object that tea dry sorting control system will acquire and yellow leaf
It encloses and is matched, confirm that each object belongs to tealeaves, tea stalk, yellow leaf or other.
In whole process, known to step A in finished tea the database of tealeaves, tea stalk and yellow leaf foundation, be based on people
Work is by tealeaves, tea stalk and yellow leaf good sorting；And the matching process of step C characteristics of objects parameter, it is by machinery to made tea
Each object in leaf is classified according to the difference of characteristic parameter.
It step B, in finished tea in the acquisition process of characteristics of objects parameter, include first step, as object
RGB original color image obtains.And the RGB original color image acquisition methods of object are, finished tea is put in a vibration
On device platform, as vibrator vibrates, the skewed slot even drop down that finished tea is 30 ° -70 ° along gradient, into CCD coloured silk
The shooting area of form and aspect machine obtains RGB original color image by CCD color camera.After RGB original color image obtains, by it
It is input in tea dry sorting control system and is handled, subsequent several steps can be completed by tea dry sorting control system,
Extract the characteristic parameter based on HSV color image.
In the RGB original color image acquisition process of object, plane where skewed slot should be with the camera plane of CCD color camera
Vertically, and space wall locating for skewed slot and CCD color camera is black entirely.
In the RGB original color image acquisition process of object, the background of CCD color camera uses the conduct of flannelette acrylic board
Background board, light source use colour temperature for the area source of 5000k-6000k.
In the RGB original color image acquisition process of object, imaged with the shooting of industrial line array CCD color camera by camera
The finished tea in region obtains its pixel data, then by pixel data carry out processing be converted into it is defeated after RGB original color image
Enter tea dry sorting control system.
RGB original color image filtering and noise reduction pretreatment specific method is, using adaptive-filtering and histogram equalization
Method is filtered noise suppression preprocessing to RGB original color image.
In the acquisition process of characteristics of objects parameter, after characteristic parameter obtains, tea dry sorting control system passes through form
Processing, eliminates region ineligible in HSV color image, and qualified characteristics of image is identified, then
Qualified image features are matched with database again.The size difference of each tealeaves will not in finished tea
Very big, tea stalk is also to be compared by size in this way, be advantageous in that by Morphological scale-space there are also yellow leaf, can by it is some not
It is that the part of tealeaves, tea stalk and yellow leaf directly weeds out, these substances directly weeded out do not need to carry out scheming based on HSV again
The characteristic parameter of picture matches.For example, if tealeaves conveying or remove it is remote during, can generate some tealeaves powders, tealeaves powder it is big
Small difference of comparing with tealeaves, tea stalk and yellow leaf is very big, this when passes through Morphological scale-space, it was found from the comparison i.e. of its size
The road tealeaves powder is not belonging to any type in tealeaves, tea stalk and yellow leaf, to be divided into other one kind.This
Sample, in the characteristic parameter matching process of subsequent progress, there is no need to carry out the characteristic parameter of the tealeaves powder and database
It has matched, to reduce the workload of tea dry sorting control system.Realize the classification of tealeaves, tea stalk, yellow leaf and other materials
It collects.
The high speed spray valve and tealeaves feed chute are coplanar, are located at the flat lower section in camera shooting area.Valve pair is sprayed using high speed
In tealeaves, tea stalk, yellow leaf and other materials assorting room, it can include and take the problem of comparing out of.It is both to sort out tea stalk
When, part tealeaves can inevitably be taken out of together.Under normal circumstances, recognizer is taken out of than meeting the requirements.If band
Ratio is relatively low out, then can be neglected, can be on tea stalk, yellow leaf and other materials channel if taking out of than relatively high
Industrial line array CCD color camera and high speed spray valve are set again, repeat the work of step B and C, until taking out of than lower than setting ratio
Thus.And take out of than be it is how many, can be measured by multiple trial operation, or by tea dry sorting control system to CCD colour
The image of camera shooting is analyzed to obtain.
Step A, in sample finished tea in the establishment process of the database of tealeaves, tea stalk and yellow leaf, and it is color using CCD
Form and aspect machine is shot, and shooting environmental is identical as the shooting environmental in the acquisition process of step B characteristics of objects parameter.
Step C, in the matching process of characteristic parameter, after the attribute confirmation of object, tea dry sorting control system control one
Group high speed spray valve events, using high speed spray valve change yellow leaf, tea stalk and other materials landing direction so that tealeaves, tea stalk,
Yellow leaf and other materials are landed from different channels respectively.
For the finished tea of same type, only need early period to establish a database, and be saved to tea dry sorting control
In system processed.Later period, then when needing to sort the finished tea of same type, that is, can skip this mistake of Database
Journey, the characteristic parameter for directly carrying out unknown tealeaves obtains and the matching process of characteristic parameter.The finished product of so-called same type
Tealeaves refers mainly to the tealeaves of the identical type produced using identical production method and its technique.
Claims (10)
1. a kind of tealeaves recognition methods based on image procossing, it is characterised in that: this method includes the foundation of database, object spy
It levies the acquisition of parameter and the matching of characteristic parameter, specific steps includes:
A, the foundation of database
(A1) the RGB original color image of sample tealeaves, tea stalk and yellow leaf is obtained；
(A2) RGB original color image is made into filtering and noise reduction pretreatment；
(A3) HSV color space will be transformed into from RGB color by pretreated RGB original color image form HSV
Color image；
(A4) the tone H of tealeaves, tea stalk and yellow leaf HSV color image, the characteristic parameter of saturation degree S, lightness V are extracted；
(A5) according to the characteristic parameter of the tone H of tealeaves, tea stalk and yellow leaf, saturation degree S, lightness V, respective tone is determined
H, the upper and lower limit value of saturation degree S, lightness V, so that it is determined that the respectively value range of tone H, saturation degree S, lightness V；
(A6) by the tea dry sorting control system of determining value range typing tea dry sorting equipment, database is constituted；
B, the acquisition of characteristics of objects parameter
Tealeaves to sub-sieve is put into tea dry sorting equipment, in tealeaves transmission process, step (A1) is repeated to (A4), passes through
The characteristic parameter of tea dry sorting control system acquisition object；
C, the matching of characteristic parameter
The characteristic parameter for the object that will acquire is matched with the value range of tealeaves, tea stalk and yellow leaf in database, is confirmed
Object belongs to tealeaves, tea stalk, yellow leaf or other.
2. the tealeaves recognition methods according to claim 1 based on image procossing, it is characterised in that: the RGB of object is original
Color image acquisition methods are that finished tea is put on a vibrator platform, as vibrator vibrates, finished tea along
The skewed slot even drop down that gradient is 30 ° -70 ° obtains RGB by CCD color camera into the shooting area of CCD color camera
Original color image.
3. the tealeaves recognition methods according to claim 2 based on image procossing, it is characterised in that: the RGB of object is original
In color image acquisition process, plane where skewed slot is vertical with the camera plane of CCD color camera, and skewed slot and CCD colour phase
Space wall locating for machine is black entirely.
4. the tealeaves recognition methods according to claim 2 based on image procossing, it is characterised in that: the RGB of object is original
In color image acquisition process, the background of CCD color camera using flannelette acrylic board as background board, light source use colour temperature for
The area source of 5000k-6000k.
5. the tealeaves recognition methods according to claim 2 based on image procossing, it is characterised in that: the RGB of object is original
In color image acquisition process, the finished tea of camera imaging area is passed through with the shooting of industrial line array CCD color camera, obtains it
Then pixel data carries out pixel data inputting tea dry sorting control system after processing is converted into RGB original color image.
6. the tealeaves recognition methods according to claim 1 based on image procossing, it is characterised in that: RGB original color figure
It is as filtering and noise reduction pre-processes specific method, using adaptive-filtering and histogram equalization method to RGB original color image
It is filtered noise suppression preprocessing.
7. the tealeaves recognition methods according to claim 1 based on image procossing, it is characterised in that: characteristics of objects parameter
In acquisition process, after characteristic parameter obtains, by Morphological scale-space, area ineligible in HSV color image is eliminated
Domain, and qualified characteristics of image is identified, then qualified image features and database are carried out again
Matching.
8. the tealeaves recognition methods according to claim 2 based on image procossing, it is characterised in that: the RGB of object is original
After color image obtains, it is input in tea dry sorting control system and is handled, extracted based on HSV color image
Characteristic parameter.
9. the tealeaves recognition methods according to claim 1 based on image procossing, it is characterised in that: step C, characteristic parameter
Matching process in, after the confirmation of the attribute of object, tea dry sorting control system controls one group of high speed spray valve events, utilizes high speed
The direction that valve changes yellow leaf, tea stalk and other materials landing is sprayed, so that tealeaves, tea stalk, yellow leaf and other materials are from difference
Channel landing.
10. the tealeaves recognition methods according to claim 9 based on image procossing, it is characterised in that: the high speed sprays valve
It is coplanar with tealeaves feed chute, it is located at the flat lower section in camera shooting area.
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| CN113477555A (en) * | 2021-07-22 | 2021-10-08 | 西华大学 | Fresh tea sorting machine based on image processing |
| CN116809388A (en) * | 2023-08-30 | 2023-09-29 | 山东浏园生态农业股份有限公司 | Intelligent tea screening method and system |
| CN116809388B (en) * | 2023-08-30 | 2023-11-07 | 山东浏园生态农业股份有限公司 | Intelligent tea screening method and system |
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